| Literature DB >> 35624334 |
Labib Shahid1, James Rice2, Haben Berhane3,4, Cynthia Rigsby5, Joshua Robinson5, Lindsay Griffin5, Michael Markl3,4, Alejandro Roldán-Alzate2,6,7.
Abstract
4D Flow MRI is a diagnostic tool that can visualize and quantify patient-specific hemodynamics and help interventionalists optimize treatment strategies for repairing coarctation of the aorta (COA). Despite recent developments in 4D Flow MRI, shortcomings include phase-offset errors, limited spatiotemporal resolution, aliasing, inaccuracies due to slow aneurysmal flows, and distortion of images due to metallic artifact from vascular stents. To address these limitations, we developed a framework utilizing Computational Fluid Dynamics (CFD) with Adaptive Mesh Refinement (AMR) that enhances 4D Flow MRI visualization/quantification. We applied this framework to five pediatric patients with COA, providing in-vivo and in-silico datasets, pre- and post-intervention. These two data sets were compared and showed that CFD flow rates were within 9.6% of 4D Flow MRI, which is within a clinically acceptable range. CFD simulated slow aneurysmal flow, which MRI failed to capture due to high relative velocity encoding (Venc). CFD successfully predicted in-stent blood flow, which was not visible in the in-vivo data due to susceptibility artifact. AMR improved spatial resolution by factors of 101 to 103 and temporal resolution four-fold. This computational framework has strong potential to optimize visualization/quantification of aneurysmal and in-stent flows, improve spatiotemporal resolution, and assess hemodynamic efficiency post-COA treatment.Entities:
Keywords: 4D flow MRI; Adaptive mesh refinement; Computational fluid dynamics; Congenital heart disease; Patient-specific
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Year: 2022 PMID: 35624334 DOI: 10.1007/s10439-022-02980-7
Source DB: PubMed Journal: Ann Biomed Eng ISSN: 0090-6964 Impact factor: 3.934